Age related declines in lean body mass become pathologically significant as osteoporosis, leading to fractures and sarcopenia, leading to muscle weakness and loss of function. These changes in body composition are ultimately associated with declines in physical function and the ability to perform tasks of daily living. The Health ABC study is a longitudinal study of 3,075 men and women aged 70-79 (52 percent women and 42 percent African American) with state of the art measures of body composition, strength and function. In Health ABC cohort, we will estimate the contribution of variation at 50 physiological candidate genes on bone (bone mineral density and bone quality) and muscle (muscle mass, strength and quality) phenotypes and performance. We will: (1) evaluate the association of muscle and bone phenotypes with variation in loci involved in six steroid metabolism and action and in growth factor and cytokine structure and action; (2) evaluate the association between candidate gene variation and annualized changes in quantitative measures of muscle and bone phenotypes; (3) evaluate the interaction between genes and between genes and environments in influencing muscle and bone phenotypes; and (4) examine the association between variation at candidate genes and measures of performance. High throughput genotyping will use the recently developed fluorescence polarization technique. To examine the relationship between musculoskeletal phenotypes and genetic polymorphisms, we will use statistical models appropriate for cross-sectional and longitudinal data. For cross-sectional analyses, our major tools will be general linear model (regression, ANOVA, and MANOVA). Main effects, interactions and planned contrasts will be assessed. Residuals, outliers and influential points will be examined and sensitivity analyses performed. For longitudinal data analysis of continuous outcomes, will employ standards random effects models. The models account for heterogeneity between subjects and consequently increase the precision with which genetic effects are measured. We will employ a general analytic method for association studies, genomic control, to make our conclusions robust against the impact of population substructure. These studies will contribute to our knowledge of the mechanisms of age related loss of lean body mass and may identify individuals at elevated risk for preventive intervention.